Motion estimation and compensation has proven to be an effective method to reduce the overall bit rate of video sequences. Motion estimation is a process for estimating the motion of image samples (e.g., pixels) between frames. Using motion estimation, the encoder attempts to match blocks of pixels in one frame with corresponding pixels in another frame. After the most similar block is found in a given search area, the change in position of the corresponding pixels is approximated and represented as motion data, such as a motion vector. Motion compensation is a process for determining a predicted image and computing the error between the predicted image and the original image. Using motion compensation, the encoder applies the motion data to an image and computes a predicted image. The difference between the predicted image and the input image is called the error signal.
Conventional motion estimation and compensation methods have been used by various encoders (e.g., MPEG-x encoders, H.26x encoders, etc.), enabling efficient cross-time compression of single-view video sequences. However, while matches produced by these methods may be efficient from a compression perspective, they are often semantically incorrect because they need not represent the underlying “true” motion in the video sequence.